Optimizing the eHealth Services From Nonlinear System Identification of the Risks Level in Flooding Aftermaths Times in Peruvian Northwestern Cities

Published in: Innovation in Education and Inclusion : Proceedings of the 16th LACCEI International Multi-Conference for Engineering, Education and Technology
Date of Conference: July 18-20, 2018
Location of Conference: Lima, Perú
Authors: Huber Nieto-Chaupis (Universidad de Ciencias y Humanidades, PE)
Full Paper: #395


We use the so-called nonlinear system identification methodology to model the level of risk in those Peruvian northwestern cities which might be scenarios of flooding during the arrival of the ""El Niño"". Essentially, we estimate the normalized outputs of the master equation based on Volterra's integration. Because the input functions are taken as stochastic distributions, the Volterra's outputs might be perceived as a probability of risk associated to possible outbreaks of diseases such as dengue or zika. We apply this methodology to investigate the risk’s scenarios in the sectors of Catacaos and La Arena, with a population altogether of 90K habitants. Because the proximity to the Piura's river, we have estimate that a 30\% of this population is potentially sensitive to a new arrival of ""El Ni\~no"", in particular those children belonging to vulnerable areas of these districts. This result would imply the necessity of a rapid implementation of health services in the first level of attention targeting the rapid and effective assistance to vulnerable population.